Free-Bloom: Zero-Shot Text-to-Video Generator with LLM Director and LDM Animator

Text-to-video is a rapidly growing research area that aims to generate a semantic, identical, and temporal coherence sequence of frames that accurately align with the input text prompt. This study focuses on zero-shot text-to-video generation considering the data- and cost-efficient. To generate a semantic-coherent video, exhibiting a rich portrayal of temporal semantics such as the whole process of flower blooming rather than a set of "moving images", we propose a novel Free-Bloom pipeline that harnesses large language models (LLMs) as the director to generate a semantic-coherence prompt sequence, while pre-trained latent diffusion models (LDMs) as the animator to generate the high fidelity frames. Furthermore, to ensure temporal and identical coherence while maintaining semantic coherence, we propose a series of annotative modifications to adapting LDMs in the reverse process, including joint noise sampling, step-aware attention shift, and dual-path interpolation. Without any video data and training requirements, Free-Bloom generates vivid and high-quality videos, awe-inspiring in generating complex scenes with semantic meaningful frame sequences. In addition, Free-Bloom is naturally compatible with LDMs-based extensions.Comment: NeurIPS 2023; Project available at: https://github.com/SooLab/Free-Bloo

A simple risk stratification model that predicts 1-year postoperative mortality rate in patients with solid-organ cancer

This study aimed to construct a scoring system developed exclusively from the preoperative data that predicts 1-year postoperative mortality in patients with solid cancers. A total of 20,632 patients who had a curative resection for solid-organ cancers between 2007 and 2012 at Chang Gung Memorial Hospital Linkou Medical Center were included in the derivation cohort. Multivariate logistic regression analysis was performed to develop a risk model that predicts 1-year postoperative mortality. Patients were then stratified into four risk groups (low-, intermediate-, high-, and very high-risk) according to the total score (0–43) form mortality risk analysis. An independent cohort of 16,656 patients who underwent curative cancer surgeries at three other hospitals during the same study period (validation cohort) was enrolled to verify the risk model. Age, gender, cancer site, history of previous cancer, tumor stage, Charlson comorbidity index, American Society of Anesthesiologist score, admission type, and Eastern Cooperative Oncology Group performance status were independently predictive of 1-year postoperative mortality. The 1-year postoperative mortality rates were 0.5%, 3.8%, 14.6%, and 33.8%, respectively, among the four risk groups in the derivation cohort (c-statistic, 0.80), compared with 0.9%, 4.2%, 14.6%, and 32.6%, respectively, in the validation cohort (c-statistic, 0.78). The risk stratification model also demonstrated good discrimination of long-term survival outcome of the four-tier risk groups (P < 0.01 for both cohorts). The risk stratification model not only predicts 1-year postoperative mortality but also differentiates long-term survival outcome between the risk groups

Experimental pub crawl from Rayleigh–Bénard to magnetostrophic convection

The interplay between convective, rotational and magnetic forces defines the dynamics within the electrically conducting regions of planets and stars. Yet their triadic effects are separated from one another in most studies, arguably due to the richness of each subset. In a single laboratory experiment, we apply a fixed heat flux, two different magnetic field strengths and one rotation rate, allowing us to chart a continuous path through Rayleigh-Bénard convection (RBC), two regimes of magnetoconvection, rotating convection and two regimes of rotating magnetoconvection, before finishing back at RBC. Dynamically rapid transitions are determined to exist between jump rope vortex states, thermoelectrically driven magnetoprecessional modes, mixed wall- and oscillatory-mode rotating convection and a novel magnetostrophic wall mode. Thus, our laboratory 'pub crawl' provides a coherent intercomparison of the broadly varying responses arising as a function of the magnetorotational forces imposed on a liquid-metal convection system

The interaction between grinding media and collector in pyrite flotation at neutral and slightly acidic pH

Gold often coexists with pyrite as micron and submicron-inclusions and pyrite is therefore floated to maximize gold recovery in gold processing plants. In practice, different types of grinding media and a great range of pH and collector concentrations are used for pyrite flotation without scientific guidance. In this study, the effect of three different types of grinding media including forged steel, 15% chromium steel and 30% chromium steel on pyrite flotation at a range of collector (potassium amyl xanthate) concentration was investigated at pH 5.0 and 7.0, and the underpinning mechanism was determined through pulp chemistry measurement, X-Ray Photoelectron Spectroscopy (XPS) surface analysis and electrochemical measurement. It was found that grinding media had a different effect on pyrite flotation at pH 5.0 and 7.0. At pH 5.0, both iron contamination originating from grinding media and xanthate oxidation played an important role in pyrite flotation. While iron contamination on the pyrite surface depressed pyrite flotation, it might be reduced by xanthate oxidation. This explains higher pyrite flotation after grinding with chromium steel than forged steel and at a higher collector concentration. At pH 7.0, pyrite flotation was mainly controlled by xanthate concentration. At a low xanthate concentration, pyrite oxidation was the predominant anodic reaction and pyrite flotation was poor due to the inability to form dixanthogen. At a high xanthate concentration, the formation of dixanthogen became predominant, which facilitated pyrite flotation

The interaction of grinding media and collector in pyrite flotation at alkaline pH

A significant proportion of invisible gold is hosted by pyrite and the successful recovery of this gold requires a high recovery of pyrite in flotation. In the industry, the flotation of gold-bearing pyrite is operated in a broad range of pH and collector concentration with different types of grinding media. Following the previous study at pH 5.0 and 7.0, the current study investigated the interaction of grinding media with collector and its effect on pyrite flotation at pH 8.5. It was interesting to find that at the same xanthate dosage the highest pyrite flotation was achieved when forged steel, instead of 30% chrome steel, was used as the grinding media although it produced the highest quantity of iron contamination. Pulp chemistry measurement, surface analysis and electrochemical study revealed that pyrite oxidation prevailed over xanthate oxidation at pH 8.5 and pulp potential played a dominant role in pyrite flotation. At this pH, the high pulp potential generated by high chrome steel grinding media facilitated pyrite oxidation instead of xanthate oxidation, but the low pulp potential generated by forged steel grinding media still allowed xanthate oxidation, thus promoting pyrite flotation

Crack Detection in Frozen Soils Using Infrared Thermographic Camera

Frozen soils are encountered on construction sites in the polar regions or regions where artificial frozen ground (AFG) methods are used. Thus, efficient ways to monitor the behavior and potential failure of frozen soils are currently in demand. The advancement of thermographic technology presents an alternative solution as deformation occurring in frozen soils generate heat via inter-particle friction, and thus a subsequent increase in temperature. In this research, uniaxial compression tests were conducted on cylindrical frozen soil specimens of three types, namely clay, sand, and gravel. During the tests, surface temperature profiles of the specimens were recorded through an infrared video camera. The thermographic videos were analyzed, and subsequent results showed that temperature increases caused by frictional heat could be observed in all three frozen soil specimens. Therefore, increases in temperature can be deemed as an indicator for the potential failure of frozen soils and this method is applicable for monitoring purposes.</jats:p

Deep Learning-Based Thermal Image Analysis for Pavement Defect Detection and Classification Considering Complex Pavement Conditions

Automatic damage detection using deep learning warrants an extensive data source that captures complex pavement conditions. This paper proposes a thermal-RGB fusion image-based pavement damage detection model, wherein the fused RGB-thermal image is formed through multi-source sensor information to achieve fast and accurate defect detection including complex pavement conditions. The proposed method uses pre-trained EfficientNet B4 as the backbone architecture and generates an argument dataset (containing non-uniform illumination, camera noise, and scales of thermal images too) to achieve high pavement damage detection accuracy. This paper tests separately the performance of different input data (RGB, thermal, MSX, and fused image) to test the influence of input data and network on the detection results. The results proved that the fused image’s damage detection accuracy can be as high as 98.34% and by using the dataset after augmentation, the detection model deems to be more stable to achieve 98.35% precision, 98.34% recall, and 98.34% F1-score